Nonempirically Tuned Range-Separated DFT Accurately Predicts Both Fundamental and Excitation Gaps in DNA and RNA Nucleobases

Using a nonempirically tuned range-separated DFT approach, we study both the quasiparticle properties (HOMO-LUMO fundamental gaps) and excitation energies of DNA and RNA nucleobases (adenine, thymine, cytosine, guanine, and uracil). Our calculations demonstrate that a physically motivated, first principles tuned DFT approach accurately reproduces results from both experimental benchmarks and more computationally intensive techniques such as many body GW theory. Furthermore, in the same set of nucleobases, we show that the nonempirical range separated procedure also leads to significantly improved results for excitation energies compared to conventional DFT methods. The present results emphasize the importance of a nonempirically tuned range separation approach for accurately predicting both fundamental and excitation gaps in DNA and RNA nucleobases.